Testing of batch data presents a unique set of technical challenges. Conventional testing tools are typically designed to work in concert with a user interface and are not suitable for batch jobs. Testing batch data requires a significant investment of resources to manually design test scenarios and test cases with full coverage of the batch job.
Further, execution of batch job test cases typically requires intervention by a system administrator to identify data sources for the batch job files and locate the batch job data within the files. Batch job files typically do not include metadata that would enable the system to identify of the relevant data fields.
It would be desirable to provide an intelligent batch job testing system that is configured to independently generate and execute test cases for batch jobs.
It would be desirable to incorporate machine learning algorithms that would allow the system to continually improve the accuracy and efficiency of the batch job testing.